Azure Data Engineer
At a glance
Mid-level Data Engineering role at exaze. Mumbai · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build bronze, silver and gold data layers in Fabric and Databricks, then create Spark-based ingestion and transformation pipelines
- Move on-premises SQL data into Fabric or Databricks using incremental loads and change capture patterns
- Tune Delta tables and SQL workloads for performance, while shifting legacy SQL processing to Spark Lakehouse datasets
- Keep finance data products tested, monitored and aligned with data contracts, platform standards and quality expectations
- Maintain ADF, Databricks and Azure Analysis Services cubes, and collaborate with business and platform teams on improvements
What you bring
- At least six years of hands-on data engineering in SQL-intensive or enterprise data settings
- Strong Microsoft SQL Server and advanced T-SQL skills, including query tuning and performance optimization
- Practical experience with Microsoft Fabric, Lakehouse design, Spark transformations and Python notebooks
- An engineering or computer science degree, or related qualification from an accredited institution, or equivalent work experience
- Experience with data pipelines, dimensional models, semantic models and governance standards
Who this fits
This role suits a mid-level data engineer who can own governed finance data products and work with business stakeholders, analysts and a central platform team. The position is based in Mumbai and asks for experience in enterprise-scale or regulated settings; financial services experience is required.
From the employer
Job Description:
At Exaze, we constantly seek exciting talent to join an organization that believes in nurturing dreamers, innovators, and doers willing to expand their horizons in the software industry. Our cultural foundation is our competitive advantage. We diligently seek out team members with a penchant for unconventional thinking and place them in environments conducive to their growth. We embrace a flat organizational structure while prioritizing internal mobility. If you possess an entrepreneurial mindset and a keen enthusiasm for learning and collaboration, this opportunity could propel your career to new heights
We are seeking a highly skilled Data Engineer to engineer and deliver Finance (Capital &Tax) domain-aligned data products within a centrally governed Microsoft Data Platform.
Key responsibility would be to build and maintain current ADF, Databricks and Azure Analysis Services cubes. Along with building new data products in Fabric within established standards, CI/CD templates, and defined data contracts, the Data Engineer will modernize SQL-driven legacy workloads and re-engineer them into scalable Spark-based Lakehouse datasets and semantic models.
Data products are treated as managed assets — version-controlled, tested, monitored, and continuously improved to meet defined quality and performance expectations.
Candidature Requirements:
- An Engineering graduate or Postgraduate from a recognized College / University.
- Strong aptitude, logical reasoning, and analytical thinking skills
- Excellent written and verbal communication skills
- Keen attention to detail, strong problem-solving skills
- Ability to work collaboratively in cross-functional teams using agile methodologies
- A values-driven individual who can think abstractly and take ownership of their work.
The role will include:
Lakehouse Engineering in Microsoft Fabric and Databricks
- Build and maintain bronze, silver, and gold layers in Microsoft Fabric and Databricks.
- Develop ingestion and transformation pipelines using:
Notebooks & Spark (PySpark preferred)
- Implement incremental loading and change data capture patterns from on-prem SQL to Fabric or Databricks.
- Optimize Delta tables for performance and cost efficiency.
- Ensure datasets align with defined data contracts and platform standards.
Data Product Ownership
- Engineer data products that are reliable, discoverable, and consumption ready.
- Apply testing and validation to ensure data quality and integrity.
- Monitor pipeline health and performance using platform-defined observability standards.
- Contribute to continuous improvement of data products based on usage and feedback.
- Collaborate closely with business stakeholders, analysts, and the central Data Platform team.
Experience, skill and capability
- 6+ years of hands-on experience in data engineering within SQL-heavy or enterprise data environments.
- Strong expertise in Microsoft SQL Server and advanced T-SQL development, including query optimization and performance tuning.
- Practical experience working with Microsoft Fabric and Lakehouse architecture principles.
- Hands-on experience with Spark (PySpark preferred) for distributed data transformation, Python notebooks.
- Solid understanding of dimensional modeling, including star schema and Kimball-based methodologies.
- Experience in Azure Data Factory, Databricks, AAS Cubes, MS Fabric, ADLS Gen2 , Purview
- Experience designing and optimizing semantic models for enterprise analytics platforms such as Power BI.
- Experience implementing incremental loading and change data capture (CDC) patterns in hybrid environments.
- Experience building production-grade data pipelines with testing, monitoring, and CI/CD integration.
- Strong understanding of data governance principles, data contracts, and structured engineering standards.
- Experience working in enterprise-scale or regulated environments with disciplined delivery practices.
- Any financial services / banking / capital market experience
Required Qualifications
- Bachelor’s degree in computer science or related field from an accredited university and/or equivalent work experience
- Microsoft certifications (Azure Data Engineer, Fabric).
- Experience in distributed data processing environments.
- Experience in enterprise-scale or regulated environments.
- Exposure to AI/ML data preparation workflows.
Experience : 6+ Years
Job Location: Mumbai
Open Position: 1
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